A common variant near the FTO gene is linked to a small average increase in body weight and BMI by nudging appetite regulation. Most carriers never become obese — environment and behavior still matter most.
Solid lines are connections this site curates. Dashed lines mean the two ends share a research paper — worth knowing, and not a claim that one explains the other.
Obesity is shaped by hundreds of genes acting alongside diet, activity, sleep, medications, and the environment a person lives in. Of all the genes studied so far, the one most consistently and strongly linked to body weight in genome-wide studies is FTO ("fat mass and obesity-associated"), on chromosome 16. A specific marker within this gene, rs9930506, was one of the first common variants ever shown — in a 2007 study of thousands of Sardinian villagers — to nudge body mass index (BMI), weight, and hip circumference in a population.
It is important to say plainly, up front: this is a small effect. Carrying the version of this variant linked to higher weight does not mean a person is destined to develop obesity, and not carrying it is no guarantee of staying lean. Most people who carry the higher-weight-associated version of this variant never become obese, and many people without it do. This page is about a genuine, replicated, but modest statistical tendency — not a diagnosis and not a life sentence.
The FTO variant does not directly control fat storage or metabolism in any simple sense. The best evidence points to an effect on appetite regulation in the brain, particularly circuits in the hypothalamus that govern hunger and satiety signaling. People carrying the higher-weight-associated version of nearby FTO variants have, on average in study populations, reported somewhat reduced feelings of fullness after eating and a mild tendency toward higher food intake — small shifts that, compounded over years, translate into a modest average difference in body weight at the population level.
Separately, laboratory work has shown that variation in this same stretch of DNA can also affect nearby genes called IRX3 and IRX5, which influence whether developing fat cells become energy-storing ("white") fat or more metabolically active, heat-generating ("beige") fat. That mechanistic work focused on a different, nearby FTO-region SNP (rs1421085) that travels together with rs9930506 on the same stretch of inherited DNA in many people, so the two lines of evidence — brain appetite circuits and fat-cell biology — likely describe two contributing pieces of the same overall picture rather than competing explanations.
In the original 2007 Sardinian study, people who inherited two copies of the higher-weight-associated version of this specific marker had, on average, a BMI about 1.3 units higher than those with two copies of the other version — roughly the difference between, say, a BMI of 24 and a BMI of 25.3 for someone of average height. Follow-up studies in European-American and Hispanic-American populations found a similar, slightly smaller difference (roughly 1.0 BMI unit between the two extreme genotype groups). A large, closely related FTO marker studied separately found that adults who inherited two copies of its higher-weight-associated version weighed about 3 kilograms more on average, and had roughly 1.7 times higher odds of obesity, compared with people carrying no copies.
These are population averages spread across a bell curve, not individual predictions. A single common variant like this one explains only a sliver of the difference in body weight between any two people — genetics researchers estimate that all known common obesity-associated variants combined still leave most of the variation in body weight unexplained, with lifestyle, environment, and many other factors accounting for the rest.
It's worth distinguishing this common, modest-effect variant from the rare, much more disruptive gene changes that can cause severe childhood-onset obesity on their own — for example, mutations affecting the leptin or melanocortin (MC4R) appetite pathways. Those are uncommon and behave very differently in a family (often causing extreme early obesity along with other features). The FTO variant discussed here is the opposite kind of finding: extremely common, found in a large share of people across many populations, and individually weak — one contributor among hundreds of genetic and non-genetic factors rather than a determining cause.
A 2018 study of 718,734 people took a different approach: instead of the common, noncoding variants most BMI GWAS find, it went looking for rarer coding variants — changes that alter the protein itself — directly in genes affecting body weight. It found 14 such variants across 13 genes, eight of them newly implicated in human obesity. Two of the fourteen sat in genes, MC4R and KSR2, already known to cause severe obesity when more disruptively mutated — a genuine bridge between the common-variant story this page mostly tells and the rare, high-impact mutations mentioned above. One of the newly implicated genes, TCF20, is on this site.
Two more large studies refine this picture further. Winkler et al. 2015, from the GIANT consortium, screened up to 320,485 people of European descent specifically for genetic effects on BMI that change with age. They found 15 loci with a significant age-dependent effect — most of them stronger before age 50 than after — the first genome-wide evidence that a BMI variant's effect is not necessarily constant across a person's life. Justice, Ng et al. 2018 took a different approach: studying 100,418 adults in the multiethnic GERA cohort rather than a largely European-ancestry sample, they found real ancestry- and nationality-specific differences in BMI genetics and 30 more replicating loci — though, consistent with everything else on this page, adding them barely moved how much of the variation in body weight is actually explained.
Body weight is influenced by genetics, but genetics is not destiny, and no variant discussed here should be read as a verdict on anyone's body, willpower, or health. If anything, understanding that appetite regulation has a real biological, partly inherited basis can be reassuring — some people genuinely have to work harder against hunger signals than others, and that is a difference in physiology, not character. The same evidence base that identified this variant also consistently shows that diet quality, physical activity, sleep, and overall environment continue to shape body weight regardless of genotype, and several studies suggest that regular physical activity can blunt the size of FTO's effect on weight. A 2017 meta-analysis of 200,452 people tested this directly: among physically active participants, FTO's effect on BMI was attenuated by roughly 30% compared with inactive participants — the same genetic variant, behaving differently depending on how the person actually lives.
Positions joined since this page was written
What this is The text above discusses the variants this page was written around. Since then the catalogue has joined 668 more positions to it, by shared trait or shared paper. They are listed here by the paper each came from; the text does not describe them, and each variant page carries that study's own record.
Huang J et al. 2022, Nature communications rs16952522 (FTO), rs74498370 (FTO), rs112232322 (FTO), rs185004749 (FTO), rs12596054 (FTO), rs455527 (CPNE7), rs56384862 (PXK), rs6901756 (USP49), rs36120387 (near PRR13), rs111305382 (KCNQ5), rs17066856 (near MC4R), rs1477199 (RPGRIP1L) and 199 more — PMID:36581621
Sakaue S et al. 2021, Nature genetics rs1950436 (near OR7K1P), rs10237306 (near CADPS2), rs57307148 (RAD52), rs58243949 (RAB27B), rs3751859 (CMIP), rs4757142 (BMAL1), rs72820274 (near LINC01965), rs7460093 (SCRIB), rs71301804 (SFMBT1), rs2168711 (near RNU4-17P), rs1415700 (L3MBTL3), rs2489879 (near IL13RA1) and 110 more — PMID:34594039
Harris BHL et al. 2024, Scientific reports rs7206324 (FTO), rs2977324 (near HNF4G), rs75759977 (near CDK2AP1), rs141224959 (LINC01865), rs2644109 (IPO9-AS1), rs7117115 (AGBL2), rs1724557 (near RNU1-89P), rs7445169 (TMEM161B-DT), rs2115885 (TMEM161B-DT), rs1927861 (near ZNF646P1), rs140604451 (GSTM2), rs779655 (RANBP17) and 76 more — PMID:38538606
Jee YH et al. 2025, Nature communications rs7553158 (TNNI3K), rs4709745 (near QKI), rs80082351 (ZBTB20), rs72634826 (SLC35E2B), rs6772763 (BTD), rs10942650 (near PCBP2P3), rs934778 (POMC), rs1811852 (HEY2), rs72660086 (MACF1), rs12213070 (HIVEP1), rs77936594 (CHFR), rs80328470 (ASB3) and 75 more — PMID:40436827
Hawkes G et al. 2023, Diabetologia rs775208 (AARS1), rs11691869 (AFF3), rs4648450 (near TTC34), rs13210756 (PRKN), rs11951885 (near RNU6-727P), rs557951 (CADPS), rs16916303 (near RPS26P2), rs187067151 (FRG1BP), rs11633022 (ADPGK), rs4958702 (MFAP3), rs9955276 (near AIDAP3), rs17132130 (MAD1L1) and 69 more — PMID:37280435
Sidorenko J et al. 2024, Nature genetics rs4794018 (IGF2BP1), rs13218383 (near MIR3144), rs6733972 (ICA1L), rs4989244 (near NAMA), rs7965658 (POLR2KP1), rs10828248 (MLLT10), rs4606726 (PDILT), rs11152029 (RAB27B), rs171390 (DHX36), rs2012697 (LINC02796), rs2398871 (near PHF2), rs1440983 (PRKD1) and 22 more — PMID:39375568
Pulit SL et al. 2019, Human molecular genetics rs208015 (SKAP1), rs4721089 (MAD1L1), rs12022461 (NHSL3), rs79716947 (PARD3B), rs7963783 (near KSR2), rs11608710 (SOX5), rs4795195 (LINC01992), rs2172935 (IPO9), rs2640017 (near RASA2), rs2960151 (TRPS1), rs7942486 (near BMAL1), rs4432163 (near CTAGE16P) and 8 more — PMID:30239722
Akiyama M et al. 2017, Nature genetics rs6734118 (PRKD3), rs139913 (TNRC6B), rs2540034 (ADCY9), rs11130319 (NEK4), rs2033732 (LINC01419), rs2235056 (LMX1B) — PMID:28892062
Verma A et al. 2024, Science (New York, N.Y.) rs7969447 (C12orf42), rs12739556 (near EEF1A1P11), rs751414 (LINC00951), rs9380823 (near DNAH8) — PMID:39024449
Hoffmann TJ et al. 2018, Genetics rs6091540 (LINC01524), rs62034325 (near NUPR1), rs9944545 (near MC4R) — PMID:30108127
Turcot V et al. 2018, Nature genetics rs34149579 (HIP1R), rs12236219 (ZNF169), rs284860 (WBP1L) — PMID:29273807
Zhang X et al. 2025, Nature communications rs62033408 (FTO) — PMID:40216759
Fernández-Rhodes L et al. 2022, HGG advances rs9922708 (FTO) — PMID:35399580
Yang J et al. 2012, Nature rs7202116 (FTO) — PMID:22982992
Speliotes EK et al. 2010, Nature genetics rs713586 (ADCY3) — PMID:20935630
Cho HW et al. 2021, Frontiers in genetics rs1211163 (HGMA1) — PMID:34054925
Hansen MEB et al. 2026, American journal of human genetics rs113531437 (PEDS1-UBE2V1) — PMID:42586059
Nagy R et al. 2017, Genome medicine rs571835655 (near TCERG1P2) — PMID:28270201
Locke AE et al. 2015, Nature rs2121279 (LRP1B) — PMID:25673413
Jeon S et al. 2024, GigaScience rs192748045 (CTNNA3) — PMID:38626723
2026-08-12 · Hansen MEB, et al. American Journal of Human Genetics 2026, PMID:42586059
Anthropometric and cardio-metabolic trait variation and genetic associations in sub-Saharan Africa
Hansen MEB, et al. (American Journal of Human Genetics, 2026) is newly in the GWAS Catalog, with 166 associations across 21 traits — an atlas rather than a single question. The catalogue records its sample as 1,544 individuals. Of its 106 positions, 21 already have pages here — 1 on the Waist Circumference page; 1 on the Childhood Body Mass Index page; 1 on the Obesity and Body Weight page — including rs11636311 (near DUT), rs9920281 (SLC12A1), rs668316 (near LINC01491). Put together by code from the catalogue's records; for anything more, follow the link to the paper. PMID:42586059.
2026-04-08 · 23andMe Research Institute, published in Nature (GWAS of 27,885 GLP-1 drug users)
Genetic predictors of GLP1 receptor agonist weight loss and side effects
A genome-wide study of 27,885 people taking GLP-1 drugs (semaglutide, tirzepatide) found a GLP1R variant linked to an extra 0.76 kg of weight loss per copy of the effect allele (P=2.9x10-10) -- direct genetic evidence the drug's own target gene shapes how well it works, not just a co-mention. The same study tied a GIPR variant (rs1800437, profiled on this site) to worse nausea and vomiting, specifically in people taking tirzepatide.
2025-09-12 · Genome-wide association study provides novel insight into the genetic architecture of severe obesity. PLOS Genetics. 2025. DOI:10.1371/journal.pgen.1011842
Severe obesity (SevO) -- Class III (BMI>=40) and Class IV (BMI>=50) -- drives cardiovascular and cardiometabolic disease and several cancers, but remains understudied relative to BMI generally, especially in marginalized populations. This study meta-analyzed the top of the BMI distribution (>=95th percentile) and the two SevO classes across 159,359 people from 11 ancestrally diverse studies, with replication in 480,897 people across 6 more studies. It confirmed a large overlap between the genetic architecture of continuous BMI and severe obesity specifically -- meaning the same common variants driving ordinary weight variation largely explain severe obesity too, not a separate genetic category. Within that overlap, it identified and replicated three genuinely novel signals specific to severe obesity: TENM2, PLCL2 and ZNF184, all within loci already known for BMI generally but newly tied to the severe end of the distribution specifically. Combining functional mapping, polygenic risk scores and phenome-wide association analysis, the study reinforced that known downstream comorbidities and lifestyle-gene interactions apply similarly across the BMI spectrum. This site's obesity and body weight page carries 527 variants; TENM2, PLCL2 and ZNF184 are not currently among them.
2026-03-06 · Haapaniemi H et al. The genetic basis of dermatophytosis skin infection susceptibility. Nature Communications 2026, PMID:41792138
Fungal skin infection runs partly in the genes — and through obesity genes
Dermatophytosis — the fungal infection behind athlete's foot, nail fungus and ringworm — affects around 20% of the world's population. A genome-wide meta-analysis of over 250,000 cases from FinnGen, the Estonian Biobank, UK Biobank and the Million Veteran Program found 30 genome-wide significant loci, with top signals near ZNF646, HLA-DQB1, FLG, FTO, SLURP2 and KRT77, and pointed to keratin biology, the skin barrier, immune function and obesity. 19 of the study's positions already have pages here, including rs1421085 in FTO, the best-known obesity position, and five on the dermatophytosis page. PMID:41792138.
Locus and variant. rs9930506 is an intronic single-nucleotide variant within FTO (alpha-ketoglutarate-dependent dioxygenase FTO; OMIM *610966) at chromosome 16q12.2. It sits within the large first intron of FTO, a region now understood to function as a long-range regulatory element rather than to affect FTO's own enzymatic (RNA demethylase) activity directly.
Discovery and effect size. rs9930506 was identified as the lead FTO variant for body-weight traits in a genome-wide association scan of 4,741–6,148 Sardinian individuals (ages 14–102) from the Lanusei Valley (Scuteri et al., PLoS Genetics 2007; PMID 17658951; GWAS Catalog trait "Obesity-related traits," study GCST000060). It was the most significantly associated FTO SNP for BMI (p = 8.6×10⁻⁷), hip circumference (p = 3.4×10⁻⁸), and weight (p = 9.1×10⁻⁷) in that cohort. Homozygotes for the common allele versus the alternate allele (minor allele frequency ≈ 0.46 in Sardinians) differed by approximately 1.3 BMI units on average; the association replicated in independent GenNet cohorts of European-American (n=1,496) and Hispanic-American (n=839) ancestry with an approximately 1.0 BMI-unit difference between homozygote groups (combined replication p between 0.0005 and 0.001), but did not reach significance in an African-American sample, where the relevant allele frequency was lower (≈0.21) and local linkage disequilibrium patterns differ. A later multi-ancestry meta-analysis (Wojcik et al., Nature 2019; PMID 31217584), incorporating African-American, Hispanic/Latino, Asian, Native Hawaiian, and Native American ancestry cohorts, confirmed genome-wide-significant association of rs9930506 with BMI (β ≈ 0.06 BMI units per copy, 95% CI 0.048–0.076, p = 4×10⁻¹⁸ per GWAS Catalog).
Relationship to other FTO markers. rs9930506 is in strong linkage disequilibrium with rs9939609, the FTO marker used in the landmark Frayling et al. study (Science 2007; PMID 17434869), which found that the 16% of adults homozygous for its risk allele weighed about 3 kg more and had a 1.67-fold higher odds of obesity than non-carriers, with the effect detectable from age 7 onward and reflecting increased fat mass specifically rather than lean mass or height. Because these markers travel together on the same haplotype in much of the genome studied, effect-size figures reported for one closely approximate, but are not identical to, the other. In the 1000 Genomes European-ancestry panel (CEU), the two markers show r² ≈ 0.86 (Ensembl linkage disequilibrium calculator) — strong enough that effect-size estimates for one track closely with the other in European-ancestry cohorts specifically. That correlation is far weaker in populations with African ancestry (r² ≈ 0.05–0.09 in the same panel's ASW, YRI and MSL samples), part of why the association has not replicated as consistently in African-American cohorts.
Proposed mechanism. Functional work by Claussnitzer et al. (NEJM 2015; PMID 26287746) traced a causal mechanism to a different but nearby FTO-intron variant, rs1421085, showing that its risk allele disrupts a repressor binding motif (ARID5B), de-represses a preadipocyte enhancer, and roughly doubles expression of two adjacent genes, IRX3 and IRX5, during early adipocyte differentiation. This shifts precursor cells away from thermogenic ("beige/brite") fat and toward energy-storing white fat, reducing mitochondrial thermogenesis roughly fivefold in cell models; CRISPR correction of rs1421085 restored thermogenic gene expression. Because rs9930506 lies in the same regulatory haplotype block, it is generally interpreted as a marker in linkage with this regulatory mechanism rather than a demonstrated causal variant in its own right; appetite/satiety effects mediated via hypothalamic FTO/FTM circuitry have also been proposed and are not mutually exclusive with the adipocyte mechanism.
Population variation and equity caveat. Effect-allele frequency for FTO obesity-associated variants differs substantially by ancestry (common in European, South Asian, and some African populations; generally lower average BMI effect reported in East Asian cohorts for some correlated markers), and most large discovery cohorts have been of European ancestry, so caution is warranted before generalizing point estimates across all populations.
Diagnostic context. Clinical obesity is defined by BMI thresholds (BMI ≥30 kg/m² in most adult clinical guidelines) or by direct adiposity measures, never by genotype; rs9930506 and related FTO markers are population risk-modifiers used in research and polygenic risk contexts, not diagnostic or predictive tests for any individual.
What a 23andMe/AncestryDNA export or raw VCF can and can't tell you about Obesity and Body Weight comes down to these specific, well-studied positions — not a diagnosis. 1571 positions are linked to this page; the ones this page's own text discusses are shown first.
See all 1571 linked variants →
The studies behind these variants recruited participants from different ancestries — a result found in one population doesn't always transfer to another. Based on 563 of 1600 linked studies with a resolved discovery ancestry.
Databases, guidelines and references
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Obesity and Body Weight. MyGeneLog™. https://www.mygenelog.com/conditions/obesity
No. It is associated with only a small average shift in body weight — on the order of one BMI unit or a few kilograms when comparing large groups of people. Most people who carry the higher-weight-associated version never develop obesity, and many people without it do. It is a modest risk-modifier, not a diagnosis or a prediction for any one person.
It sits in a regulatory region of the FTO gene that has been linked to appetite and satiety signaling in the brain, and — through a nearby, closely linked variant — to whether developing fat cells favor energy storage or heat-generating metabolism. It does not appear to act through FTO's own enzyme function directly.
It's the most consistently replicated common obesity-associated gene found so far, but it is one of hundreds of genes with small effects on body weight, not a single dominant cause. Rare mutations in other genes (such as those in the leptin or MC4R appetite pathways) can cause severe obesity on their own, but those are uncommon and genetically distinct from this common variant.
The evidence base underlying this variant's discovery consistently shows that lifestyle factors continue to shape body weight regardless of genotype, and several studies suggest regular physical activity can blunt FTO's average effect on weight. Genetics loads the dice; it does not decide the outcome.
No. Its frequency and its measured effect size differ across ancestry groups, and most of the original discovery research was done in European and Sardinian populations. A 2019 multi-ancestry study confirmed the association in several other populations, but it was not statistically significant in an African-American sample, likely reflecting a lower allele frequency and different local genetic structure in that group.
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